Neural network mechanisms underlying stimulus driven variability reduction.
Neural network mechanisms underlying stimulus driven variability reduction.
复制标题
DOI：
10.1371/journal.pcbi.1002395
复制
发表时间：
2012
影响因子：
4.3
通讯作者：
Hugues E
中科院分区：
文献类型：
--
作者：
Deco G;Hugues E
众所周知，通过 Fano 因子测量，不同试验中神经活动的变异性有所提高。这一事实对神经活动的信息编码造成了限制。然而，最近的一系列神经生理学实验改变了这一传统观点。跨物种、大脑区域、大脑状态和刺激条件的单细胞记录表明，当施加外部刺激以及当注意力分配到神经元感受野内的刺激时，神经变异性显着减少，这表明信息编码得到增强。使用其动态表现出多个吸引子的异构连接神经网络模型，我们在这里演示了网络效应如何产生这种变异性减少。在自发状态下，我们表明高度的神经变异主要是由于吸引子之间波动驱动的偏移造成的。当在参数空间中网络工作点位于允许多稳态吸引子的分叉附近时，就会发生这种情况。通过刺激或注意力施加外部兴奋性驱动可以稳定一个特定的吸引子，从而消除不同吸引子之间的转换，并导致试验中神经变异性的净减少。重要的是，无反应神经元也表现出变异性的减少。最后，发现这种变异性的减少是由于神经尖峰序列的规律性增加所致。总之，这些结果表明刺激和注意力下变异性的减少是神经回路的一个特性。为了了解神经元如何编码信息，神经科学家记录了动物在许多试验中执行给定任务时的放电活动。令人惊讶的是，已经发现神经反应是高度可变的，这先验地限制了这些神经元对信息的编码。然而，最近的实验表明，当动物接受刺激或关注特定刺激时，这种变异性就会减少，这表明信息编码得到了增强。众所周知，神经变异的原因在于单个神经元接收到的输入在其放电阈值附近波动。我们在这里证明，所有实验结果都可以自然地源于神经网络的动力学。使用现实模型，我们表明自发活动期间的神经变异性特别高，因为输入噪声会引起多个但不稳定的网络状态之间的巨大波动。通过刺激或注意力，一种特定的网络状态会稳定下来，波动会减少，从而导致神经变异性减少。总之，我们的结果表明观察到的变异性减少是大脑神经回路的一个特性。
It is well established that the variability of the neural activity across trials, as measured by the Fano factor, is elevated. This fact poses limits on information encoding by the neural activity. However, a series of recent neurophysiological experiments have changed this traditional view. Single cell recordings across a variety of species, brain areas, brain states and stimulus conditions demonstrate a remarkable reduction of the neural variability when an external stimulation is applied and when attention is allocated towards a stimulus within a neuron's receptive field, suggesting an enhancement of information encoding. Using an heterogeneously connected neural network model whose dynamics exhibits multiple attractors, we demonstrate here how this variability reduction can arise from a network effect. In the spontaneous state, we show that the high degree of neural variability is mainly due to fluctuation-driven excursions from attractor to attractor. This occurs when, in the parameter space, the network working point is around the bifurcation allowing multistable attractors. The application of an external excitatory drive by stimulation or attention stabilizes one specific attractor, eliminating in this way the transitions between the different attractors and resulting in a net decrease in neural variability over trials. Importantly, non-responsive neurons also exhibit a reduction of variability. Finally, this reduced variability is found to arise from an increased regularity of the neural spike trains. In conclusion, these results suggest that the variability reduction under stimulation and attention is a property of neural circuits. To understand how neurons encode information, neuroscientists record their firing activity while the animal executes a given task for many trials. Surprisingly, it has been found that the neural response is highly variable, which a priori limits the encoding of information by these neurons. However, recent experiments have shown that this variability is reduced when the animal receives a stimulus or attends to a particular one, suggesting an enhancement of information encoding. It is known that a cause of neural variability resides in the fact that individual neurons receive an input which fluctuates around their firing threshold. We demonstrate here that all the experimental results can naturally arise from the dynamics of a neural network. Using a realistic model, we show that the neural variability during spontaneous activity is particularly high because input noise induces large fluctuations between multiple –but unstable- network states. With stimulation or attention, one particular network state is stabilized and fluctuations decrease, leading to a neural variability reduction. In conclusion, our results suggest that the observed variability reduction is a property of the neural circuits of the brain.
登录
查看更多内容
影响因子：
16.2
作者：
Mitchell, Jude F.;Sundberg, Kristy A.;Reynolds, John H.
通讯作者：
Reynolds, John H.
影响因子：
--
作者：
Hugues, Etienne;Jose, Jorge V.
通讯作者：
Jose, Jorge V.
影响因子：
64.8
作者：
Kenet, T;Bibitchkov, D;Arieli, A
通讯作者：
Arieli, A
DOI：
10.1073/pnas.0901831106
发表时间：
2009-06-23
影响因子：
11.1
作者：
Deco, Gustavo;Jirsa, Viktor;Koetter, Rolf
通讯作者：
Koetter, Rolf
影响因子：
2.5
作者：
Deco, G;Rolls, ET
通讯作者：
Rolls, ET